Senior AI/ML Engineer - R01572485

Brillio; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Brillio in Bengaluru, Karnataka invites a Senior AI/ML Engineer to lead the design and deployment of enterprise‑scale AI platforms. You will own model lifecycle, MLOps/LLMOps, and AI observability to ensure robust deployment and monitoring.

We seek hands‑on experts in Python, PySpark, and cloud AI stacks, with deep knowledge of Responsible AI and governance. Join a team driving reusable patterns and scalable AI solutions across business lines.

Qualifications

• 6+ years of AI/ML engineering experience.
• Designing, building, and operating enterprise-scale AI platforms.
• Hands-on with model lifecycle, MLOps/LLMOps, and AI observability.
• Strong Python and PySpark skills for data processing and modeling.
• Experience with cloud-based AI platforms and modern architectures.
• Knowledge of Responsible AI, governance, model risk, security and compliance.
• Hands-on with KubeFlow and BentoML for ML pipelines.
• Solid foundation in statistics and data analysis.

Responsibilities

• Lead design and architecture of enterprise AI platforms for scalability and security.
• Define frameworks for model lifecycle, MLOps/LLMOps, and AI observability.
• Establish Responsible AI governance and guardrails across solutions.
• Drive platform-level decisions and create reusable AI architecture patterns.
• Collaborate with business, data, technology, and platform teams to productionize AI.
• Evaluate emerging AI tech to support long-term scalability and outcomes.
• Maintain AI model governance, versioning, and documentation.

Skills

Enterprise-scale AI platform design

Model lifecycle management

MLOps/LLMOps

Python

PySpark

Cloud AI platforms

Responsible AI governance

KubeFlow

BentoML

Statistical analysis

Education

Bachelor's degree in CS/Data Science/Math

TensorFlow Developer Certificate

Azure AI Engineer Associate

IBM Data Science Professional Certificate

Tools

KubeFlow

BentoML

TensorFlow

PyTorch

Sci-Kit Learn

Keras

MXNet

Great Expectations

Evidently AI

Job description

Senior AI/ML Engineer

Job requirements

Experience Range: with at least 6 years of experience in AI/ML engineering, including hands‑on expertise in designing, building, and operationalizing enterprise‑scale AI platforms

Key Responsibilities

• Lead the design and architecture of enterprise-scale AI platforms, ensuring scalability, security, and operational readiness
• Define and implement frameworks for model lifecycle management, MLOps/LLMOps, and AI observability to support robust deployment and monitoring
• Establish and enforce Responsible AI principles, governance frameworks, and technical guardrails across AI solutions
• Drive platform-level technical decision-making and define reusable architecture patterns, standards, and reference models for AI and GenAI solutions
• Collaborate with business, data, technology, and platform teams to translate AI architecture principles into production-ready capabilities
• Evaluate emerging AI technologies and assess their applicability to enterprise AI platforms, supporting long‑term scalability and business outcomes
• Maintain and improve AI model governance, version control, and documentation for ongoing operational excellence

Required Skills

• Expertise in enterprise-scale AI platform design and operationalization
• Deep proficiency in model lifecycle management, MLOps/LLMOps, and AI observability
• Advanced programming skills in Python and PySpark
• Experience with cloud-based AI platforms and modern data/AI architectures
• Knowledge of Responsible AI, AI governance, model risk, security, and compliance
• Hands‑on experience with KubeFlow and BentoML for ML pipeline orchestration
• Competence in classification algorithms such as decision trees and SVM
• Experience with Great Expectations and Evidently AI for model validation
• Strong proficiency in regression analysis (linear and logistic)
• Statistical analysis and computing for large datasets

Preferred Skills

• Experience with GenAI architectures, large language models, and AI agents
• Proficiency in advanced ML frameworks such as TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, or MXNet
• Knowledge of vector databases and AI orchestration
• Understanding of AI observability and Responsible AI frameworks
• Experience developing reusable AI architecture patterns and accelerators

Desired Qualifications

• Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or a closely related discipline
• Certification in Machine Learning or Data Science (e.g., TensorFlow Developer Certificate, Microsoft Certified: Azure AI Engineer Associate)
• Relevant certification in statistical analysis or advanced analytics (e.g., SAS Certified Specialist, IBM Data Science Professional Certificate)